Triple

T27914588
Position Surface form Disambiguated ID Type / Status
Subject Loong Kim Sang E706033 entity
Predicate roleTypeSpecialization P163978 FINISHED
Object male impersonation roles in Cantonese opera LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: male impersonation roles in Cantonese opera | Statement: [Loong Kim Sang, roleTypeSpecialization, male impersonation roles in Cantonese opera]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: roleTypeSpecialization
Context triple: [Loong Kim Sang, roleTypeSpecialization, male impersonation roles in Cantonese opera]
  • A. positionSpecialization
    Indicates that one position is a more specialized or focused variant of another, broader position.
  • B. roleInSpecification
    Indicates that an entity participates in a specification with a particular role or function within that specification.
  • C. labelSpecialization
    Indicates that one label is a more specific or specialized version of another label within a labeling or classification system.
  • D. specialRole
    Indicates that an entity holds a distinctive or exceptional function, status, or responsibility in relation to another entity or context.
  • E. portrayedAsSpecialization
    Indicates that one entity is depicted or represented as a specialized or more specific version of another entity.
  • F. None of above. chosen

Provenance (4 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ef96b6cc808190aab19fb18b235f4b completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f6416fbf4081909b0913c337927fc4 completed May 2, 2026, 6:24 p.m.
PD Predicate disambiguation batch_69f63c6895f0819088655277e45859a8 completed May 2, 2026, 6:03 p.m.
PDg Predicate description generation batch_69f63fd4f7448190930c723ba7cfce62 completed May 2, 2026, 6:17 p.m.
Created at: April 27, 2026, 6:52 p.m.